from omegaconf import OmegaConf from query import VectaraQuery import streamlit as st import os from PIL import Image def launch_bot(): def generate_response(question): response = vq.submit_query(question) return response def reset(): st.session_state.messages = [{"role": "assistant", "content": "Please ask your question about drink names.", "avatar": '🦖'}] st.session_state.vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_id, cfg.prompt_name) if 'cfg' not in st.session_state: cfg = OmegaConf.create({ 'customer_id': str(os.environ['VECTARA_CUSTOMER_ID']), 'corpus_id': '46', # Fixed corpus ID for drink names 'api_key': str(os.environ['VECTARA_API_KEY']), 'prompt_name': 'vectara-experimental-summary-ext-2023-12-11-large', }) st.session_state.cfg = cfg st.session_state.vq = VectaraQuery(cfg.api_key, cfg.customer_id, cfg.corpus_id, cfg.prompt_name) cfg = st.session_state.cfg vq = st.session_state.vq st.set_page_config(page_title="Drink Name Query Bot", layout="wide") # Left side content with st.sidebar: image = Image.open('Vectara-logo.png') st.image(image, width=250) st.markdown(f"## Welcome to Drink Name Query Bot.\n\n\n") if st.button('Start Over'): reset() st.markdown("---") st.markdown( "## How this works?\n" "This app was built with [Vectara](https://vectara.com).\n\n" "It demonstrates the use of the Chat functionality along with custom prompts and GPT4-Turbo (as part of our [Scale plan](https://vectara.com/pricing/))" ) st.markdown("---") if "messages" not in st.session_state.keys(): reset() # Display chat messages for message in st.session_state.messages: with st.chat_message(message["role"], avatar=message["avatar"]): st.write(message["content"]) # User-provided prompt if prompt := st.chat_input(): st.session_state.messages.append({"role": "user", "content": prompt, "avatar": '🧑‍💻'}) with st.chat_message("user", avatar='🧑‍💻'): st.write(prompt) # Generate a new response if last message is not from assistant if st.session_state.messages[-1]["role"] != "assistant": with st.chat_message("assistant", avatar='🤖'): response = generate_response(prompt) st.write(response) message = {"role": "assistant", "content": response, "avatar": '🤖'} st.session_state.messages.append(message) if __name__ == "__main__": launch_bot()